7 citations · 7 across the 8 of their papers we have counts for
9 papers
Challenges in Explaining Pretrained Clinical Text Classifiers
Kristian Miok, Matej Klemen, Blaz Škrlj +1
Explaining the predictions of neural models in clinical NLP remains a significant challenge, especially for complex tasks involving long, unstructured medical texts. While post-hoc…
QFS-Composer: Query-focused summarization pipeline for less resourced languages
Vuk Đuranović, Marko Robnik Šikonja
Large language models (LLMs) demonstrate strong performance in text summarization, yet their effectiveness drops significantly across languages with restricted training resources.…
Incremental Graph Construction Enables Robust Spectral Clustering of Texts
Marko Pranjić, Boshko Koloski, Nada Lavrač +2
Neighborhood graphs are a critical but often fragile step in spectral clustering of text embeddings. On realistic text datasets, standard -NN graphs can contain many disconnecte…
Large language models for folktale type automation based on motifs: Cinderella case study
Tjaša Arčon, Marko Robnik-Šikonja, Polona Tratnik
Artificial intelligence approaches are being adapted to many research areas, including digital humanities. We built a methodology for large-scale analyses in folkloristics. Using m…
TT-XAI: Trustworthy Clinical Text Explanations via Keyword Distillation and LLM Reasoning
Kristian Miok, Blaz Škrlj, Daniela Zaharie +1
Clinical language models often struggle to provide trustworthy predictions and explanations when applied to lengthy, unstructured electronic health records (EHRs). This work introd…
Real-time News Story Identification
Tadej Škvorc, Nikola Ivačič, Sebastjan Hribar +1
To improve the reading experience, many news sites organize news into topical collections, called stories. In this work, we present an approach for implementing real-time story ide…
Solving Word-Sense Disambiguation and Word-Sense Induction with Dictionary Examples
Tadej Škvorc, Marko Robnik-Šikonja
Many less-resourced languages struggle with a lack of large, task-specific datasets that are required for solving relevant tasks with modern transformer-based large language models…
Sarcasm Detection in a Less-Resourced Language
Lazar Đoković, Marko Robnik-Šikonja
The sarcasm detection task in natural language processing tries to classify whether an utterance is sarcastic or not. It is related to sentiment analysis since it often inverts sur…
Retrieval-augmented code completion for local projects using large language models
Marko Hostnik, Marko Robnik-Šikonja
The use of large language models (LLMs) is becoming increasingly widespread among software developers. However, privacy and computational requirements are problematic with commerci…